Data Engineer

Manulife•Waterloo, ON

5d•$86,100 - $136,100•Hybrid

About The Position

The ideal candidate for a Data Engineer role is someone with strong programming skills, experience with database management systems, and a deep understanding of ETL (Extract, Transform, Load) and EDL processes. They should also have excellent problem-solving skills and the ability to collaborate effectively in a team-oriented environment!

Requirements

5 to 7 years of experience in data engineering or a related field.
3 to 5 years of experience in developing and managing Azure Data Pipelines.
Demonstrable experience with Databricks, including building and maintaining data pipelines.
Proficient in ETL (Extract, Transform, Load) processes and standard methodologies.
Experience with Informatica for data integration and transformation tasks.
Proficiency in using reporting tools like Power BI and Cognos for data visualization and reporting.
Solid understanding of data architecture and database management systems.
Strong programming skills in languages such as Python, SQL, or Scala.
Excellent problem-solving abilities and attention to detail.
Ability to work collaboratively in a team-oriented setting and communicate effectively with technical and non-technical collaborators.
Experience with data quality and data governance practices to ensure data integrity and security across the organization.
Familiarity with performance monitoring and optimization techniques for large-scale data systems.

Nice To Haves

Master's degree in Computer Science, Engineering, or a related field

Responsibilities

Building and maintaining robust and scalable data pipelines that automate the collection, transformation, and storage of data from various sources.
Ensuring seamless integration of data from different sources into a unified data warehouse or data lake, facilitating easy access and analysis.
Designing, implementing, and managing databases and data storage solutions that can handle large volumes of data efficiently.
Putting in place systems and resources to secure the correctness, uniformity, and safeguarding of data company-wide.
Monitoring system performance and making improvements as needed to ensure data systems are running efficiently and effectively.
Working with data scientists, analysts, and other collaborators to understand data requirements and deliver solutions that meet business needs.
Staying up to date with emerging technologies and tools in data engineering and recommending their adoption where appropriate to improve data processes and infrastructure.